Similar with the approaches in [1]}, a variance reduction technique is used. With the \(k^{th}\)  mini-batch, the moving average baseline is estimated as an accumulation of the previous log-likelihoods with exponential decay:
\(b_k = 0.9 \times b_{k-1} + 0.1 \times log\ p(y|\tilde{l}_k,a)\) 
